class_docstr: A mix-in class for storing tensors as properties with helper methods.
docstr: In place operation to move class properties which are tensors to a
  specified device. If self has a property "device", update this as well.
docstr_tok: ["In","place","operation","to","move","class","properties","which","are","tensors","to","a","specified","device",".","If","self","has","a","property","``","device","''",",","update","this","as","well","."]
code: def to(self, device: Device = "cpu") -> "TensorProperties":
      """
      In place operation to move class properties which are tensors to a
      specified device. If self has a property "device", update this as well.
      """
      device_ = make_device(device)
      for k in dir(self):
          v = getattr(self, k)
          if k == "device":
              setattr(self, k, device_)
          if torch.is_tensor(v) and v.device != device_:
              setattr(self, k, v.to(device_))
      return self
  
imports: import copy
  import inspect
  import warnings
  from typing import Any, List, Optional, Tuple, TypeVar, Union
  import numpy
  import torch
  import torch.nn
  from ..common.datatypes import Device, make_device
label_desc: Use image node_id 5 for calling the TensorProperties obj's underlying member method code with example usage: obj.to(device) and returns: self